TY - JOUR

T1 - Multiscale finite element methods for high-contrast problems using local spectral basis functions

AU - Efendiev, Yalchin R.

AU - Galvis, Juan

AU - Wu, Xiao-Hui

N1 - KAUST Repository Item: Exported on 2020-10-01
Acknowledged KAUST grant number(s): KUS-C1-016-04
Acknowledgements: The work of Y.E. and J.G. is partially supported by Award Number KUS-C1-016-04, made by King Abdullah University of Science and Technology (KAUST). Y.E.'s research is partially supported by NSF (0724704, 0811180, 0934837) and DOE. We would like to thank the anonymous reviewers for their suggestions that helped to improve the paper.
This publication acknowledges KAUST support, but has no KAUST affiliated authors.

PY - 2011/2

Y1 - 2011/2

N2 - In this paper we study multiscale finite element methods (MsFEMs) using spectral multiscale basis functions that are designed for high-contrast problems. Multiscale basis functions are constructed using eigenvectors of a carefully selected local spectral problem. This local spectral problem strongly depends on the choice of initial partition of unity functions. The resulting space enriches the initial multiscale space using eigenvectors of local spectral problem. The eigenvectors corresponding to small, asymptotically vanishing, eigenvalues detect important features of the solutions that are not captured by initial multiscale basis functions. Multiscale basis functions are constructed such that they span these eigenfunctions that correspond to small, asymptotically vanishing, eigenvalues. We present a convergence study that shows that the convergence rate (in energy norm) is proportional to (H/Λ*)1/2, where Λ* is proportional to the minimum of the eigenvalues that the corresponding eigenvectors are not included in the coarse space. Thus, we would like to reach to a larger eigenvalue with a smaller coarse space. This is accomplished with a careful choice of initial multiscale basis functions and the setup of the eigenvalue problems. Numerical results are presented to back-up our theoretical results and to show higher accuracy of MsFEMs with spectral multiscale basis functions. We also present a hierarchical construction of the eigenvectors that provides CPU savings. © 2010.

AB - In this paper we study multiscale finite element methods (MsFEMs) using spectral multiscale basis functions that are designed for high-contrast problems. Multiscale basis functions are constructed using eigenvectors of a carefully selected local spectral problem. This local spectral problem strongly depends on the choice of initial partition of unity functions. The resulting space enriches the initial multiscale space using eigenvectors of local spectral problem. The eigenvectors corresponding to small, asymptotically vanishing, eigenvalues detect important features of the solutions that are not captured by initial multiscale basis functions. Multiscale basis functions are constructed such that they span these eigenfunctions that correspond to small, asymptotically vanishing, eigenvalues. We present a convergence study that shows that the convergence rate (in energy norm) is proportional to (H/Λ*)1/2, where Λ* is proportional to the minimum of the eigenvalues that the corresponding eigenvectors are not included in the coarse space. Thus, we would like to reach to a larger eigenvalue with a smaller coarse space. This is accomplished with a careful choice of initial multiscale basis functions and the setup of the eigenvalue problems. Numerical results are presented to back-up our theoretical results and to show higher accuracy of MsFEMs with spectral multiscale basis functions. We also present a hierarchical construction of the eigenvectors that provides CPU savings. © 2010.

UR - http://hdl.handle.net/10754/598916

UR - https://linkinghub.elsevier.com/retrieve/pii/S0021999110005292

UR - http://www.scopus.com/inward/record.url?scp=78650565921&partnerID=8YFLogxK

U2 - 10.1016/j.jcp.2010.09.026

DO - 10.1016/j.jcp.2010.09.026

M3 - Article

VL - 230

SP - 937

EP - 955

JO - Journal of Computational Physics

JF - Journal of Computational Physics

SN - 0021-9991

IS - 4

ER -